Instructions to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M
# Run inference directly in the terminal:
llama cli -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Use Docker

docker model run hf.co/sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

LM Studio
Jan
Ollama
How to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with Ollama:
```
ollama run hf.co/sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M
```
Unsloth Desktop

How to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with Docker Model Runner:
```
docker model run hf.co/sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M
```

Lemonade

How to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Run and chat with the model

lemonade run user.Ornith-1.5-REAP-20B-A3B-GGUF-Q5_K_M

List all available models

lemonade list

Hermes Agent

How to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "sleepyeldrazi/Ornith-1.5-REAP-20B-A3B-GGUF:Q5_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

sleepy commited on 14 days ago

Commit

bee3dcd

1 Parent(s): 61175f7

Update README: quant-convention filenames + repeat-penalty serving tip

Browse files

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -43,9 +43,9 @@ and quantizations calibrated on agentic-coding / ML-engineering data.
 | file | what | size |
 |---|---|---|
 | `BF16/` | full-precision (BF16) reaped+recovered checkpoint | 36 GB |
-| `GGUFs/q5k_ud.gguf` | **recommended** — Q5_K_M + UD-style important-tensor raises, domain imatrix | 14.3 GB |
-| `GGUFs/q5k_plain.gguf` | Q5_K_M, domain imatrix, no tensor map | 13.6 GB |
-| `GGUFs/ud_iq4nl.gguf` | IQ4_NL + IQ3_S/IQ4_NL expert map (smallest) | 10.5 GB |
 | `GGUFs/recovered-f16.gguf`, `GGUFs/reap-only-f16.gguf` | F16 reference GGUFs (pre/post recovery) | 38.1 GB each |
 For IQ quantizations of the *un-pruned* 35B base, see

 | file | what | size |
 |---|---|---|
 | `BF16/` | full-precision (BF16) reaped+recovered checkpoint | 36 GB |
+| `GGUFs/Ornith-1.5-REAP-20B-A3B-UD-Q5_K_M.gguf` | **recommended** — Q5_K_M + UD-style important-tensor raises, domain imatrix | 14.3 GB |
+| `GGUFs/Ornith-1.5-REAP-20B-A3B-Q5_K_M.gguf` | Q5_K_M, domain imatrix, no tensor map | 13.6 GB |
+| `GGUFs/Ornith-1.5-REAP-20B-A3B-UD-IQ4_NL.gguf` | IQ4_NL + IQ3_S/IQ4_NL expert map (smallest) | 10.5 GB |
 | `GGUFs/recovered-f16.gguf`, `GGUFs/reap-only-f16.gguf` | F16 reference GGUFs (pre/post recovery) | 38.1 GB each |
 For IQ quantizations of the *un-pruned* 35B base, see